After REINFORCE implementation, redesign the learning process and NN architecture design to leverage conceptual processes like bagging, stacking, boosting,etc. in an RL setting.
REINFORCE algorithm will provide a strong baseline in lunarlander environment. From there, we can experiment with the ensembled experts to learn using a novel policy gradient algorithm.
Extensive testing and alterations will occur in this issue's associated branch.
After REINFORCE implementation, redesign the learning process and NN architecture design to leverage conceptual processes like bagging, stacking, boosting,etc. in an RL setting.
REINFORCE algorithm will provide a strong baseline in lunarlander environment. From there, we can experiment with the ensembled experts to learn using a novel policy gradient algorithm.
Extensive testing and alterations will occur in this issue's associated branch.